Correlation Between Bank Danamon and Bank Jabar
Can any of the company-specific risk be diversified away by investing in both Bank Danamon and Bank Jabar at the same time? Although using a correlation coefficient on its own may not help to predict future stock returns, this module helps to understand the diversifiable risk of combining Bank Danamon and Bank Jabar into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Bank Danamon Indonesia and Bank Jabar, you can compare the effects of market volatilities on Bank Danamon and Bank Jabar and check how they will diversify away market risk if combined in the same portfolio for a given time horizon. You can also utilize pair trading strategies of matching a long position in Bank Danamon with a short position of Bank Jabar. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bank Danamon and Bank Jabar.
Diversification Opportunities for Bank Danamon and Bank Jabar
0.78 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Bank and Bank is 0.78. Overlapping area represents the amount of risk that can be diversified away by holding Bank Danamon Indonesia and Bank Jabar in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Bank Jabar and Bank Danamon is a relative statistical measure of the degree to which these equity instruments tend to move together. The correlation coefficient measures the extent to which returns on Bank Danamon Indonesia are associated (or correlated) with Bank Jabar. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Bank Jabar has no effect on the direction of Bank Danamon i.e., Bank Danamon and Bank Jabar go up and down completely randomly.
Pair Corralation between Bank Danamon and Bank Jabar
Assuming the 90 days trading horizon Bank Danamon Indonesia is expected to under-perform the Bank Jabar. But the stock apears to be less risky and, when comparing its historical volatility, Bank Danamon Indonesia is 1.22 times less risky than Bank Jabar. The stock trades about -0.31 of its potential returns per unit of risk. The Bank Jabar is currently generating about -0.24 of returns per unit of risk over similar time horizon. If you would invest 98,000 in Bank Jabar on August 26, 2024 and sell it today you would lose (3,500) from holding Bank Jabar or give up 3.57% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Bank Danamon Indonesia vs. Bank Jabar
Performance |
| Timeline |
| Bank Danamon Indonesia |
| Bank Jabar |
Bank Danamon and Bank Jabar Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Bank Danamon and Bank Jabar
The main advantage of trading using opposite Bank Danamon and Bank Jabar positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bank Danamon position performs unexpectedly, Bank Jabar can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Bank Jabar will offset losses from the drop in Bank Jabar's long position.| Bank Danamon vs. Bank Cimb Niaga | Bank Danamon vs. Indosat Tbk | Bank Danamon vs. Astra Agro Lestari | Bank Danamon vs. Bank Mandiri Persero |
| Bank Jabar vs. Bank Pembangunan Timur | Bank Jabar vs. Bank Tabungan Negara | Bank Jabar vs. Bank Danamon Indonesia | Bank Jabar vs. Bumi Serpong Damai |
Check out your portfolio center.Note that this page's information should be used as a complementary analysis to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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